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Showing 106 to 120 of 227 results Save | Export
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Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric – Journal of Experimental Education, 2015
This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…
Descriptors: Effect Size, Measurement Techniques, Statistical Analysis, Research Design
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Ugille, Maaike; Moeyaert, Mariola; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim – Journal of Experimental Education, 2014
A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…
Descriptors: Effect Size, Statistical Bias, Sample Size, Regression (Statistics)
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Finch, W. Holmes; French, Brian F. – Educational and Psychological Measurement, 2012
Effect size use has been increasing in the past decade in many research areas. Confidence intervals associated with effect sizes are encouraged to be reported. Prior work has investigated the performance of confidence interval estimation with Cohen's d. This study extends this line of work to the analysis of variance case with more than two…
Descriptors: Computation, Statistical Analysis, Effect Size, Comparative Analysis
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Ishak, Noriah Mohd; Abu Bakar, Abu Yazid – World Journal of Education, 2014
Due to statistical analysis, the issue of random sampling is pertinent to any quantitative study. Unlike quantitative study, the elimination of inferential statistical analysis, allows qualitative researchers to be more creative in dealing with sampling issue. Since results from qualitative study cannot be generalized to the bigger population,…
Descriptors: Case Studies, Statistical Analysis, Sampling, Qualitative Research
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Yoon, Jae ho; Lee, Ji hae; Lee, Chae Yeon; Cho, Minhee; Lee, Sang Min – Asia Pacific Education Review, 2014
The purpose of the current study is to demonstrate a significant suppressor effect among coping strategies on resilience. Two different samples were used to replicate the suppressor effect. Participants in the first example were 391 adolescents (middle school students) in Korea, and participants in the second example were 282 young adults…
Descriptors: Foreign Countries, Coping, Resilience (Psychology), Adolescents
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Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M. – Journal of Educational Data Mining, 2015
The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…
Descriptors: Undergraduate Students, Graduate Students, Academic Achievement, Prediction
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O'Hara, Michael E. – Journal of Economic Education, 2014
Although the concept of the sampling distribution is at the core of much of what we do in econometrics, it is a concept that is often difficult for students to grasp. The thought process behind bootstrapping provides a way for students to conceptualize the sampling distribution in a way that is intuitive and visual. However, teaching students to…
Descriptors: Economics Education, Economics, Sampling, Statistical Inference
Goodwyn, Fara – Online Submission, 2012
Exploratory factor analysis involves five key decisions. The second decision, how many factors to retain, is the focus of the current paper. Extracting too many or too few factors often leads to devastating effects on study results. The advantages and disadvantages of the most effective and/or most utilized strategies to determine the number of…
Descriptors: Syntax, Factor Analysis, Research Methodology, Statistical Analysis
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Collins, Kathleen M. T.; Onwuegbuzie, Anthony J. – New Directions for Evaluation, 2013
The goal of this chapter is to recommend quality criteria to guide evaluators' selections of sampling designs when mixing approaches. First, we contextualize our discussion of quality criteria and sampling designs by discussing the concept of interpretive consistency and how it impacts sampling decisions. Embedded in this discussion are…
Descriptors: Sampling, Mixed Methods Research, Evaluators, Q Methodology
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Brett, Zoe H.; Sheridan, Margaret; Humphreys, Kate; Smyke, Anna; Gleason, Mary Margaret; Fox, Nathan; Zeanah, Charles; Nelson, Charles; Drury, Stacy – International Journal of Behavioral Development, 2015
An individual's neurodevelopmental and cognitive sequelae to negative early experiences may, in part, be explained by genetic susceptibility. We examined whether extreme differences in the early caregiving environment, defined as exposure to severe psychosocial deprivation associated with institutional care compared to normative rearing,…
Descriptors: Genetics, Institutionalized Persons, Residential Care, Cognitive Processes
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Varzande, Mohsen; Jadidi, Esmaeil – English Language Teaching, 2015
Translators differ from each other in many ways in terms of their knowledge and professional conditions that may directly influence their translation. The present study aimed at investigating the impact of translators' academic experience on their translation quality. Following a "causal-comparative study", a sample of 100 male and…
Descriptors: Translation, Educational Attainment, Educational Quality, Sampling
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Herzog, Stefan M.; Hertwig, Ralph – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Individuals can partly recreate the "wisdom of crowds" within their own minds by combining nonredundant estimates they themselves have generated. Herzog and Hertwig (2009) showed that this accuracy gain could be boosted by urging people to actively think differently when generating a 2nd estimate ("dialectical bootstrapping").…
Descriptors: Sampling, Statistical Inference, Experimental Psychology, Hypothesis Testing
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Michaelides, Michalis P.; Haertel, Edward H. – Applied Measurement in Education, 2014
The standard error of equating quantifies the variability in the estimation of an equating function. Because common items for deriving equated scores are treated as fixed, the only source of variability typically considered arises from the estimation of common-item parameters from responses of samples of examinees. Use of alternative, equally…
Descriptors: Equated Scores, Test Items, Sampling, Statistical Inference
Woodruff, David; Wu, Yi-Fang – ACT, Inc., 2012
The purpose of this paper is to illustrate alpha's robustness and usefulness, using actual and simulated educational test data. The sampling properties of alpha are compared with the sampling properties of several other reliability coefficients: Guttman's lambda[subscript 2], lambda[subscript 4], and lambda[subscript 6]; test-retest reliability;…
Descriptors: Sampling, Test Reliability, Item Response Theory, Statistical Inference
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Padilla, Miguel A.; Divers, Jasmin – Educational and Psychological Measurement, 2013
The performance of the normal theory bootstrap (NTB), the percentile bootstrap (PB), and the bias-corrected and accelerated (BCa) bootstrap confidence intervals (CIs) for coefficient omega was assessed through a Monte Carlo simulation under conditions not previously investigated. Of particular interests were nonnormal Likert-type and binary items.…
Descriptors: Sampling, Statistical Inference, Computation, Statistical Analysis
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